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Adaptive neuro-fuzzy vibration control of a smart plate

Muradova Aliki, Tairidis Georgios, Stavroulakis Georgios

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URI: http://purl.tuc.gr/dl/dias/F317B83D-71AB-4CEA-B0EF-1790CCA5408A
Year 2017
Type of Item Peer-Reviewed Journal Publication
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Bibliographic Citation A. D. Muradova, G. K. Tairidis and G. E. Stavroulakis, "Adaptive neuro-fuzzy vibration control of a smart plate," Numer. Algebra Contr. Optim., vol. 7, no. 3, pp. 251-271, Sept. 2017. doi: 10.3934/naco.2017017 https://doi.org/10.3934/naco.2017017
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Summary

In the present paper, the vibration supression of a smart plate with the use of ANFIS (Adaptive Neuro-Fuzzy Inference System) is investigated. The whole system consists of a nonlinear mechanical model, which is an extension of the von Kármán plate model with control. The structure is subjected to external disturbances and generalized control forces. Initial and boundary conditions are set up. The initial boundary value problem is spatially-discretized by a time spectral method. The obtained discretized mod-el is a system of nonlinear ordinary differential equations (ODEs) with respect to time. A neuro-fuzzy inference system is built and tested in order to create a nonlinear controller for the vibration supression of the plate. More specifically, a Sugeno-type fuzzy inference system is employed and trained through ANFIS. The inputs of the controller are the displacement and the velocity and the out-put is the control force. An effective optimization procedure is proposed and numerical results are presented. © 2017 Federacion Argentina de Cardiologia.

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